A new study from West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI) uses a wearable device and artificial intelligence (AI) to predict COVID-19 up to 3 days before symptoms occur. The study has been an impressive undertaking involving over 1000 health care workers and frontline workers in hospitals across New York, Philadelphia, Nashville, and other critical COVID-19 hotspots.

The implementation of the digital health platform uses a custom smartphone application coupled with an Ōura smart ring to monitor biometric signals such as respiration and temperature. The platform also assesses psychological, cognitive, and behavioral data through surveys administered through a smartphone application.

We know that wearables tend to suffer from a lack of accuracy, particularly during activity. However, the Ōura ring appears to take measurements while the user is very still, especially during sleep. This presents an advantage as the accuracy of wearable devices greatly improves when the user isn’t moving. RNI noted that the Ōura ring has been the most accurate device they have tested.

Given some of the early warning signals for COVID-19 are fever and respiratory distress, it would make sense that a device able to measure respiration and temperature could be used as an early detector of COVID-19. In fact, we’ve seen a few wearable device companies attempt much of what RNI is doing as well as a few DIY attempts. RNI’s study has probably been the most thorough work released so far, but we’re sure that many more are upcoming.

The initial phase of the study was deployed among healthcare and frontline workers but is now open to the general public. Meanwhile the National Basketball Association (NBA) is coordinating its re-opening efforts using Ōura’s technology.

We hope to see more results emerge from RNI’s very important work. Until then, stay safe Hackaday.

source https://hackaday.com/2020/07/11/detect-covid-19-symptoms-using-wearable-device-and-ai/

A new study from West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI) uses a wearable device and artificial intelligence (AI) to predict COVID-19 up to 3 days before symptoms occur. The study has been an impressive undertaking involving over 1000 health care workers and frontline workers in hospitals across New York, Philadelphia, Nashville, and other critical COVID-19 hotspots.

The implementation of the digital health platform uses a custom smartphone application coupled with an Ōura smart ring to monitor biometric signals such as respiration and temperature. The platform also assesses psychological, cognitive, and behavioral data through surveys administered through a smartphone application.

We know that wearables tend to suffer from a lack of accuracy, particularly during activity. However, the Ōura ring appears to take measurements while the user is very still, especially during sleep. This presents an advantage as the accuracy of wearable devices greatly improves when the user isn’t moving. RNI noted that the Ōura ring has been the most accurate device they have tested.

Given some of the early warning signals for COVID-19 are fever and respiratory distress, it would make sense that a device able to measure respiration and temperature could be used as an early detector of COVID-19. In fact, we’ve seen a few wearable device companies attempt much of what RNI is doing as well as a few DIY attempts. RNI’s study has probably been the most thorough work released so far, but we’re sure that many more are upcoming.

The initial phase of the study was deployed among healthcare and frontline workers but is now open to the general public. Meanwhile the National Basketball Association (NBA) is coordinating its re-opening efforts using Ōura’s technology.

We hope to see more results emerge from RNI’s very important work. Until then, stay safe Hackaday.

source https://hackaday.com/2020/07/11/detect-covid-19-symptoms-using-wearable-device-and-ai/

A new study from West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI) uses a wearable device and artificial intelligence (AI) to predict COVID-19 up to 3 days before symptoms occur. The study has been an impressive undertaking involving over 1000 health care workers and frontline workers in hospitals across New York, Philadelphia, Nashville, and other critical COVID-19 hotspots.

The implementation of the digital health platform uses a custom smartphone application coupled with an Ōura smart ring to monitor biometric signals such as respiration and temperature. The platform also assesses psychological, cognitive, and behavioral data through surveys administered through a smartphone application.

We know that wearables tend to suffer from a lack of accuracy, particularly during activity. However, the Ōura ring appears to take measurements while the user is very still, especially during sleep. This presents an advantage as the accuracy of wearable devices greatly improves when the user isn’t moving. RNI noted that the Ōura ring has been the most accurate device they have tested.

Given some of the early warning signals for COVID-19 are fever and respiratory distress, it would make sense that a device able to measure respiration and temperature could be used as an early detector of COVID-19. In fact, we’ve seen a few wearable device companies attempt much of what RNI is doing as well as a few DIY attempts. RNI’s study has probably been the most thorough work released so far, but we’re sure that many more are upcoming.

The initial phase of the study was deployed among healthcare and frontline workers but is now open to the general public. Meanwhile the National Basketball Association (NBA) is coordinating its re-opening efforts using Ōura’s technology.

We hope to see more results emerge from RNI’s very important work. Until then, stay safe Hackaday.

source https://hackaday.com/2020/07/11/detect-covid-19-symptoms-using-wearable-device-and-ai/

Foam is certainly an indispensable raw material for various craft and construction projects. Any serious sculptor however, inevitably grows tired of grinding through a foam block using a simple preheated utensil. The next step up, is to assemble a simple but thoroughly effective hot wire cutting contraption, formed out of a thin guitar wire held taut on a “C” shaped mounting frame. Finally, the addition of some electronics to regulate the power delivery makes this simple tool useful for most settings.

[Freddie] has taken this basic idea a step further, by building a complete multi-axis CNC foam cutter intended as an interactive exhibit on computational art. The CNC has the traditional three Cartesian axes but the platform hosting the foam piece can also rotate, introducing an additional degree of freedom. As this is indented to be controlled by attendees, there is no G-code in the mix, rather the inputs of an Xbox controller are applied directly to the work piece.

What is very interesting is how the resulting tool path is visualised and displayed. [Freddie] explains that while the user input tool path could be generated and displayed as equivalent G-code, it does not capture and convey the inherent organic nature of the finished pieces. The solution [Freddie] came up with is to display the toolpath much like a series of musical notes!

We would have loved to have a go at this machine in person, but seeing that isn’t possible in the current circumstances, you can either build a simpler machine we featured earlier or [Freddie] could perhaps fire up a camera and let us control it via the interweb, with a live video feed ofcourse!

source https://hackaday.com/2020/07/11/interactive-cnc-foam-cutter-churns-out-abstract-art/

Bats use echolocation to see objects in front of them. They emit an ultrasonic pulse around 20 kHz (and up to 100 kHz) and then sense the pulses as they reflect off an object and back to the bat. It’s the same type of mechanism used by ultrasonic proximity sensors for object-avoidance. Humans (except perhaps the very young ones) can’t hear the ultrasonic pulses since the frequency is too high, but an inexpensive microphone in a simple bat detector could. As it turns out bat detectors are available off the shelf, but where’s the fun in that? So, like any good hacker, [WilkoL] decided to build his own.

[WilkoL’s] design is composed primarily of an electret microphone, microphone preamplifier, CD4040 binary counter, LM386 audio amplifier, and a speaker. Audio signals are analog and their amplitudes vary based on how close the sound is to the microphone. [WilkoL] wanted to pick up bat sounds as far away as possible, so he cranked up the gain of the microphone preamplifier by quite a bit, essentially railing the amplifiers. Since he mostly cares about the frequency of the sound and not the amplitude, he wasn’t concerned about saturating the transistor output.

The CD4040 then divides the signal by a factor of 16, generating an output signal within the audible frequency range of the human ear. A bat signal of 20 kHz divides down to 1.25 kHz and a bat signal of up to 100 kHz divides down to 6.25 kHz.

He was able to test his bat detector with an ultrasonic range finder and by the noise generated from jingling his keychain (apparently there are some pretty non-audible high-frequency components from jingling keys), but hasn’t been able to pick up any bats as yet. Maybe somewhat ironically, there aren’t a ton of bats in his neighborhood.

Anyway, we’re definitely looking forward to seeing the bat detector in action! Who knows, maybe he’ll find Batman.

source https://hackaday.com/2020/07/11/hack-together-your-own-bat-signal/

We don’t know if aerodynamics is really a subject for dummies, per se, but if you are interested in flying or building drones and model aircraft, [Jenny Ma’s] new video that you can see below will help you get an easy introduction to some key concepts. (Embedded below.)

The show starts with coverage of lift, thrust, and drag, but moves on to topics such as stalling and coffin corners. If you have a pilot ticket, you might not learn a lot of new things, but for the rest of us, there are some interesting nuggets that you might not have known or might have forgotten from your physics classes in high school.

Actually, some of us are old enough that we learned an incorrect theory of how wings generate lift in school, and [Jenny] covers that and explains how we now know that the cause and effect of that theory were backward.

Speaking of bad theories, the video covers subsonic flight, although there is a little discussion of supersonic flight. Remember that before the X1 broke the sound barrier in 1947, many people thought it was not possible to do that.

This video won’t prepare you for designing the next jumbo jet or X1, but it might just help you next time you want to build a novel quadcopter or even a paper airplane.

source https://hackaday.com/2020/07/11/aerodynamics-for-dummies/

Reading Hackaday is great! You get so many useful tips from watching other people work, it’s truly changed nearly everything about the way I hack, especially considering that I’ve been reading Hackaday for the past 15 years. Ideas, freely shared among peers, are the best of the free and open-source hardware community. But there’s a dark downside: I’m going CNC mill shopping.

It all started with [Robin]’s excellent video and website tutorial on his particular PCB DIY procedures. You see, I love making PCBs at home, because I’m unafraid of chemistry, practiced with a rolling pin and iron, and super-duper impatient. If I can get a board done today, I’m not waiting a week, even if that means an hour of work on my part.

Among other things, he’s got this great technique with a scriber pen and a cleverly designed registration base that make it easy for him to do nearly perfectly aligned two-sided boards with a resolution approaching etching. The ability to make easy double-sided boards, with holes drilled, makes milling attractive, but the low resolution of v-cutter milled boards has been the show-stopper for me. If that’s gone, maybe it’s time to take a serious look.

And heck, making PCBs is really just the tip of the iceberg for what I’d want to do with a CNC mill. Currently, I do dodgy metalworking with an x-y table and a drill press, some of which may someday land me in the hospital. But if I had a mill, I’d be doing all sorts of funny wood joinery and who knows what else. I lack experience with a mill, but coincidentally, we just had a Hack Chat on Linux for machine tools this week. You see? It’s all conspiring against me.

The only question left is what I should get. I’m looking at the ballscrew 3040 range of CNCs, and maybe upgrading the spindle. I’d like to mill up to aluminum, but don’t really need steel. What do you think?

source https://hackaday.com/2020/07/11/hackaday-made-me-buy-it/

Reading Hackaday is great! You get so many useful tips from watching other people work, it’s truly changed nearly everything about the way I hack, especially considering that I’ve been reading Hackaday for the past 15 years. Ideas, freely shared among peers, are the best of the free and open-source hardware community. But there’s a dark downside: I’m going CNC mill shopping.

It all started with [Robin]’s excellent video and website tutorial on his particular PCB DIY procedures. You see, I love making PCBs at home, because I’m unafraid of chemistry, practiced with a rolling pin and iron, and super-duper impatient. If I can get a board done today, I’m not waiting a week, even if that means an hour of work on my part.

Among other things, he’s got this great technique with a scriber pen and a cleverly designed registration base that make it easy for him to do nearly perfectly aligned two-sided boards with a resolution approaching etching. The ability to make easy double-sided boards, with holes drilled, makes milling attractive, but the low resolution of v-cutter milled boards has been the show-stopper for me. If that’s gone, maybe it’s time to take a serious look.

And heck, making PCBs is really just the tip of the iceberg for what I’d want to do with a CNC mill. Currently, I do dodgy metalworking with an x-y table and a drill press, some of which may someday land me in the hospital. But if I had a mill, I’d be doing all sorts of funny wood joinery and who knows what else. I lack experience with a mill, but coincidentally, we just had a Hack Chat on Linux for machine tools this week. You see? It’s all conspiring against me.

The only question left is what I should get. I’m looking at the ballscrew 3040 range of CNCs, and maybe upgrading the spindle. I’d like to mill up to aluminum, but don’t really need steel. What do you think?

source https://hackaday.com/2020/07/11/hackaday-made-me-buy-it/